The Verge: “Academic writing often has a reputation for being hard to follow, but what if you could use machine learning to summarize arguments in scientific papers so that even a seven-year-old could understand them? That’s the idea behind tl;dr papers — a project that leverages recent advances in AI language processing to simplify science. Work on the site began two years ago by university friends Yash Dani and Cindy Wu as a way to “learn more about software development,” Dani tells The Verge, but the service went viral on Twitter over the weekend when academics started sharing AI summaries of their research. The AI-generated results are sometimes inaccurate or simplified to the point of idiocy. But just as often, they are satisfyingly and surprisingly concise, cutting through academic jargon to deliver what could be mistaken for child-like wisdom. Take this summary of a paper by Professor Michelle Ryan, director of the Global Institute for Women’s Leadership at the Australian National University. Ryan has written on the concept of the “glass cliff,” a form of gender discrimination in which women are placed in leadership roles at times when institutions are at their greatest risk of failure. The AI summary of her work? “The glass cliff is a place where a lot of women get put. It’s a bad place to be.” “It is just excellent,” as Ryan put it.